Birst transforms the way people work with data by delivering fast, trusted insights through an adaptive user experience that helps information consumers become information producers. Watch this video to learn more:
HR analytics is attracting a lot of attention. Last year, Towers Watson found that one in three organisations planned to increase spend on their HR function by more than 20 percent, and HR data and analytics tools rated as one of ...
Marketing analytics is a developing discipline that has real potential to affect how companies perform over time. Technology and market research firm Forrester Research predicts that companies will increase their investments in data and analytic technologies during 2016 to gain better ...
When it comes to business intelligence (BI), the struggle is classic: Centralized IT is concerned with data governance, whereas users want freedom to access data quickly. While keeping up with the breakneck pace of the modern business landscape requires on-demand intelligence, IT departments are hesitant to let go of the strong governance structures that legacy BI platforms boast.
If your legacy on-premises business intelligence (BI) solution is insufficient for your needs, consider cloud BI as a more agile alternative. According to The Forrester Wave™: Cloud Business Intelligence Platforms, Q4 2015, “vendors that combine the advantages of cloud delivery with enterprise BI features offer optimal platforms to their customers.”
Traditionally, most Business Intelligence (BI) and analytics solutions have offered separate products for dashboards and discovery that are clearly aimed at specific audiences. Dashboards are typically used by ‘information consumers,’ those who monitor their business regularly.
In my last piece on how businesses use data, I outlined a maturity model for taking up analytics across an organisation. However, while this approach works at the strategic level, there are opportunities for BI teams to more quickly increase the value that projects deliver as well. This is based on making analytics more agile.